ArticleLaboratory investigation; a journal of technical methods and pathology2015
Investigation of the potential of Raman spectroscopy for oral cancer detection in surgical margins.
Article in Laboratory investigation; a journal of technical methods and pathology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.
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Who cites it
30 citing papers in PubMed, 1 synthesis or guideline pooled it, 81 citations in OpenAlex.
- Diagnostic accuracy of Raman spectroscopy in oral squamous cell carcinoma.Frontiers in oncology · 2022Pooled it
- The Substrate-Engine Model of Ferroptosis: Stage-Specific Targeting of Acyl-CoA Synthetase Long-Chain Family Member 4 and 5‑Lipoxygenase in Alzheimer's Disease.ACS pharmacology & translational science · 2026Review
- Establishment of a clinical workflow for in vivo Raman spectroscopy during head and neck cancer surgery.Scientific reports · 2025Article
- Article
- Portable System for In-Clinic Differentiation of Skin Cancers from Benign Skin Lesions and Inflammatory Dermatoses.JID innovations : skin science from molecules to population health · 2024Article
- Cancer diagnosis using label-free SERS-based exosome analysis.Theranostics · 2024Review
- Raman spectroscopy to discriminate laryngeal squamous cell carcinoma from non-cancerous surrounding tissue.Lasers in medical science · 2023Article
- Stimulated Raman histology for histological evaluation of oral squamous cell carcinoma.Clinical oral investigations · 2023Article
- Eugene Nicholas Myers' Lecture on Head and Neck Cancer, 2020: The Surgeon as a Prognostic Factor in Head and Neck Cancer Patients Undergoing Surgery.International archives of otorhinolaryngology · 2023Article
- A New Detection Method of Oral and Oropharyngeal Squamous Cell Carcinoma Based on Multivariate Analysis of Surface Enhanced Raman Spectra of Salivary Exosomes.Journal of personalized medicine · 2023Article
- Review
- Rapid multi-task diagnosis of oral cancer leveraging fiber-optic Raman spectroscopy and deep learning algorithms.Frontiers in oncology · 2023Article
- Raman microspectroscopy fingerprinting of organoid differentiation state.Cellular & molecular biology letters · 2022Article
- Raman Spectroscopy: A Novel Technology for Gastric Cancer Diagnosis.Frontiers in bioengineering and biotechnology · 2022Review
- A New Look into Cancer-A Review on the Contribution of Vibrational Spectroscopy on Early Diagnosis and Surgery Guidance.Cancers · 2021Review
- Risk prediction by Raman spectroscopy for disease-free survival in oral cancers.Lasers in medical science · 2021Article
- Qualitative and Quantitative Diagnosis in Head and Neck Cancer.Diagnostics (Basel, Switzerland) · 2021Review
- Bimodal multispectral imaging system with cloud-based machine learning algorithm for real-time screening and detection of oral potentially malignant lesions and biopsy guidance.Journal of biomedical optics · 2021Article
- Raman spectroscopy and artificial intelligence to predict the Bayesian probability of breast cancer.Scientific reports · 2021Article
- The Potential of Raman Spectroscopy in the Diagnosis of Dysplastic and Malignant Oral Lesions.Cancers · 2021Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The poor prognosis of oral cavity squamous cell carcinoma (OCSCC) patients is associated with residual tumor after surgery. Raman spectroscopy has the potential to provide an objective intra-operative evaluation of the surgical margins. Our aim was to understand the discriminatory basis of Raman spectroscopy at a histological level. In total, 127 pseudo-color Raman images were generated from unstained thin tissue sections of 25 samples (11 OCSCC and 14 healthy) of 10 patients. These images were clearly linked to the histopathological evaluation of the same sections after hematoxylin and eosin-staining. In this way, Raman spectra were annotated as OCSCC or as a surrounding healthy tissue structure (i.e., squamous epithelium, connective tissue (CT), adipose tissue, muscle, gland, or nerve). These annotated spectra were used as input for linear discriminant analysis (LDA) models to discriminate between OCSCC spectra and healthy tissue spectra. A database was acquired with 88 spectra of OCSCC and 632 spectra of healthy tissue. The LDA models could distinguish OCSCC spectra from the spectra of adipose tissue, nerve, muscle, gland, CT, and squamous epithelium in 100%, 100%, 97%, 94%, 93%, and 75% of the cases, respectively. More specifically, the structures that were most often confused with OCSCC were dysplastic epithelium, basal layers of epithelium, inflammation- and capillary-rich CT, and connective and glandular tissue close to OCSCC. Our study shows how well Raman spectroscopy enables discrimination between OCSCC and surrounding healthy tissue structures. This knowledge supports the development of robust and reliable classification algorithms for future implementation of Raman spectroscopy in clinical practice.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.